107 research outputs found
Generic model for experimenting and using a family of classifiers systems: description and basic applications.
International audienceClassifiers systems are tools adapted to learn interactions between autonomous agents and their environments. However, there are many kinds of classifiers systems which differ in subtle technical ways. This article presents a generic model (called GEMEAU) that is common to the major kinds of classifiers systems. GEMEAU was developed for different simple applications which are also described
Characterization of different DLC and DLN electrodes for biosensor design
International audienceDiamond-Like Carbon and Carbon-Like Nanocomposite electrodes, novel materials in the field of biosensors, made with different ratio of sp3/sp2 carbon hybridization or doped with elements such as Ni, Si and W, were characterized electrochemically by cyclic voltammetry and by amperometric measurements towards hydrogen peroxide. SiCAr1 and SiCNi5% were chosen as sensitive transducers for elaboration of amperometric glucose biosensors. Immobilization of glucose oxidase was carried out by cross-linking with glutareldehyde. Measurements were made at a fixed potential + 1.0 V in 40 mM phosphate buffer pH 7.4. SiCAr1 seems to be more sensitive for glucose (0.6875 ”A/mM) then SiCNi5% (0.3654 ”A/mM). Detections limits were respectively 20 ”M and 30 ”M. Michaelis-Menten constants for the two electrodes were found around 3 mM. 48% and 79% of the original response for 0.5 mM glucose remained respectively for both electrodes after 10 days
Neuroevolutionary reinforcement learning for generalized control of simulated helicopters
This article presents an extended case study in the application of neuroevolution to generalized simulated helicopter hovering, an important challenge problem for reinforcement learning. While neuroevolution is well suited to coping with the domainâs complex transition dynamics and high-dimensional state and action spaces, the need to explore efficiently and learn on-line poses unusual challenges. We propose and evaluate several methods for three increasingly challenging variations of the task, including the method that won first place in the 2008 Reinforcement Learning Competition. The results demonstrate that (1) neuroevolution can be effective for complex on-line reinforcement learning tasks such as generalized helicopter hovering, (2) neuroevolution excels at finding effective helicopter hovering policies but not at learning helicopter models, (3) due to the difficulty of learning reliable models, model-based approaches to helicopter hovering are feasible only when domain expertise is available to aid the design of a suitable model representation and (4) recent advances in efficient resampling can enable neuroevolution to tackle more aggressively generalized reinforcement learning tasks
Environmental Factors in the Relapse and Recurrence of Inflammatory Bowel Disease:A Review of the Literature
The causes of relapse in patients with Crohn's disease (CD) and ulcerative colitis (UC) are largely unknown. This paper reviews the epidemiological and clinical data on how medications (non-steroidal anti-inflammatory drugs, estrogens and antibiotics), lifestyle factors (smoking, psychological stress, diet and air pollution) may precipitate clinical relapses and recurrence. Potential biological mechanisms include: increasing thrombotic tendency, imbalances in prostaglandin synthesis, alterations in the composition of gut microbiota, and mucosal damage causing increased permeability
Rebound growth of BRAF mutant pediatric glioma cells after MAPKi withdrawal is associated with MAPK reactivation and secretion of microglia-recruiting cytokines
INTRODUCTION:
Patients with pediatric low-grade gliomas (pLGGs), the most common primary brain tumors in children, can often benefit from MAPK inhibitor (MAPKi) treatment. However, rapid tumor regrowth, also referred to as rebound growth, may occur once treatment is stopped, constituting a significant clinical challenge.
METHODS:
Four patient-derived pediatric glioma models were investigated to model rebound growth in vitro based on viable cell counts in response to MAPKi treatment and withdrawal. A multi-omics dataset (RNA sequencing and LC-MS/MS based phospho-/proteomics) was generated to investigate possible rebound-driving mechanisms. Following in vitro validation, putative rebound-driving mechanisms were validated in vivo using the BT-40 orthotopic xenograft model.
RESULTS:
Of the tested models, only a BRAFV600E-driven model (BT-40, with additional CDKN2A/Bdel) showed rebound growth upon MAPKi withdrawal. Using this model, we identified a rapid reactivation of the MAPK pathway upon MAPKi withdrawal in vitro, also confirmed in vivo. Furthermore, transient overactivation of key MAPK molecules at transcriptional (e.g. FOS) and phosphorylation (e.g. pMEK) levels, was observed in vitro. Additionally, we detected increased expression and secretion of cytokines (CCL2, CX3CL1, CXCL10 and CCL7) upon MAPKi treatment, maintained during early withdrawal. While increased cytokine expression did not have tumor cell intrinsic effects, presence of these cytokines in conditioned media led to increased attraction of microglia cells in vitro.
CONCLUSION:
Taken together, these data indicate rapid MAPK reactivation upon MAPKi withdrawal as a tumor cell intrinsic rebound-driving mechanism. Furthermore, increased secretion of microglia-recruiting cytokines may play a role in treatment response and rebound growth upon withdrawal, warranting further evaluation
The HEV Ventilator
HEV is a low-cost, versatile, high-quality ventilator, which has been
designed in response to the COVID-19 pandemic. The ventilator is intended to be
used both in and out of hospital intensive care units, and for both invasive
and non-invasive ventilation. The hardware can be complemented with an external
turbine for use in regions where compressed air supplies are not reliably
available. The standard modes provided include PC-A/C(Pressure Assist
Control),PC-A/C-PRVC(Pressure Regulated Volume Control), PC-PSV (Pressure
Support Ventilation) and CPAP (Continuous Positive airway pressure). HEV is
designed to support remote training and post market surveillance via a web
interface and data logging to complement the standard touch screen operation,
making it suitable for a wide range of geographical deployment. The HEV design
places emphasis on the quality of the pressure curves and the reactivity of the
trigger, delivering a global performance which will be applicable to ventilator
needs beyond theCOVID-19 pandemic. This article describes the conceptual design
and presents the prototype units together with their performance evaluation.Comment: 34 pages, 18 figures, Extended version of the article submitted to
PNA
- âŠ